A new model for structural damage assessment using adaptive mutation particle swarm optimization and support vector machine

Abstract

Structural damage assessment is an important part of structural health monitoring. Nevertheless, there is the defect of low accuracy in the existed evaluation methods. In order to solve this problem, a new model for structural damage assessment using adaptive mutation Particle Swarm Optimization(AMPSO) and Support Vector Machine(SVM) named A-SVM model is proposed in this paper. Firstly, A-SVM model uses AMPSO algorithm to calculate the best parameters of SVM, and then the optimized SVM model is adopted to evaluate the structural damage. A-SVM model and other two different models are used to assess the structural damages of a pile structure as an experiment, the results show that A-SVM model has a higher prediction accuracy than SVM model and PSO-SVM model.